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However, if data is a DataFrame, then data['a'] returns all values in the column(s) named a. To avoid this ambiguity, Pandas supports the syntax data.loc['a'] as an alternative way to filter using the index. Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a ...
The <> type represents inner nodes, and is pronounced conc, inspired by :: (the cons type) in functional lists, used for sequential programming.. Concatenation in O(log n) time then works by ensuring that the difference in levels (i.e. heights) between any two sibling trees is one or less, similar to invariants maintained in AVL trees.
The strings over an alphabet, with the concatenation operation, form an associative algebraic structure with identity element the null string—a free monoid. Sets of strings with concatenation and alternation form a semiring, with concatenation (*) distributing over alternation (+); 0 is the empty set and 1 the set consisting of just the null ...
Rexx uses this syntax for concatenation including an intervening space. C (along with Python) allows juxtaposition for string literals, however, for strings stored as character arrays, the strcat function must be used. COBOL uses the STRING statement to concatenate string variables. MATLAB and Octave use the syntax "[x y]" to concatenate x and y.
Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;
Serial concatenated convolutional codes were first analyzed with a view toward turbo decoding in "Serial Concatenation of Interleaved Codes: Performance Analysis, Design, and Iterative Decoding" by S. Benedetto, D. Divsalar, G. Montorsi and F. Pollara. [4]
A concatenative programming language is a point-free computer programming language in which all expressions denote functions, and the juxtaposition of expressions denotes function composition. [1]
Range concatenation grammar (RCG) is a grammar formalism developed by Pierre Boullier [1] in 1998 as an attempt to characterize a number of phenomena of natural language, such as Chinese numbers and German word order scrambling, which are outside the bounds of the mildly context-sensitive languages.